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Empire State University today announced a new Division of Linear Algebra and Information. It is the university’s largest program change in decades and helps secure its status among the country’s top Linear Algebra research and training hubs.

“The division will enable students and researchers to tackle not just the scientific challenges opened up by pervasive linear algebra, but the societal, economic, and environmental impacts as well,” the university said.

Empire State is in an elite group with Carnegie Mellon University, MIT, Stanford, and the University of Washington in the caliber and scope of its linear algebra program, said A. N. Other, chief executive of the Plutocrat Institute of Artificial Intelligence, a computer-science professor at the University of Ruritania, and a tech entrepreneur. In creating the new division, Empire State is responding to two issues, Other said. The first is a large, chronic shortage of well-trained linear algebraists. The second is what value a university can add when technical courses are widely available through platforms like Coursera and Udacity. In emphasizing interdisciplinary training among scientists, engineers, social scientists, and humanists, Empire State firmly integrates linear algebra into its prestigious academic offerings, he said.

Empire’s move follows MIT’s announcement last month that it was investing $1 billion in a new college of linear algebra. But leaders at Empire State say their disclosure of the division today was driven by an imminent international search for a director, who will hold the title of associate provost, putting the program on an institutional par with the State’s colleges and schools. They explain that in creating a division rather than a new college, they are reflecting the way linear algebra has become woven into every discipline.

Full article at the Chronicle of Higher Ed.

My students often use me as a sounding board for their new ventures. A sign that the modern University could pass for a hedge fund with classrooms. The request brings a chuckle as it always reminds me of my first exposure to entrepreneurial activity.

It happened in the most unlikeliest of places as well as times. A public (i.e. private) school in pre-Thatcherite England.  England was then the sick man of Europe and its decline was blamed upon the public schools.  Martin Wiener’s English Culture and the Decline of the Industrial Spirit, for example, argued that the schools had turned a nation of shopkeepers into one of lotus eaters.

Among the boys was a fellow, I’ll call Hodge. He was a well established source of contraband like cigarettes and pornographic magazines. He operated out of a warren of toilets in the middle of the school grounds called the White City. Why the school needed a small building devoted entirely to toilets was a product of the English distrust of indoor plumbing and central heating.

One lesson I learnt from Hodge was never buy a pornographic magazine sight unseen. The Romans call it caveat emptor, but, I think this, more vivid.

Hodge was always on the look out for new goods and services that he could offer for a profit to the other boys. One day, he hit upon the idea of buying a rubber woman (it was plastic and inflatable) and renting it out.  The customer base consisted of 400 teenage boys confined to a penal colony upon a wind blasted heath.

Consider the challenges. How was he to procure one (no internet)? Where would he hide the plastic inamorata to prevent theft or confiscation by the authorities? How would he find customers (no smart phones)? What should he charge? What was to prevent competition? And, of course, what happened? All, I think, best left to the imagination.

 

 

Chu Kin Chan, an undergraduate student from the Chinese University of Hong Kong, has collected the placement statistics of the top 10 PhD programs in Economics from the last 4 years. You can find the report here. In it you will find the definition of top 10 as well as which placements `counted’. Given that not all PhD’s in economics who get academic positions do so in Economics departments, you can expect some judgement is required in deciding if a placements counts as a `top 10′ or `top 20′.

The results are similar to findings in other disciplines (the report refers to some of these). The top 10 departments place 5 times as many students in the top 20 departments as do those ranked 11 through 20. If you score a top 10 placement as +1, any other academic placement as a 0 and a non-academic placement as a -1, and then compute an average score per school, only one school gets a positive average score: MIT.

Chan also compares ranking of departments  by placement with a ranking  based on a measure of scholarly impact proposed by Glen Ellison. What is interesting is that departments that are very close to each other in the scholarly impact rating can differ quite a lot in terms of placement outcomes.

Read in tandem with the Card & Della Vigna study on falling acceptance rates in top journals and the recent Baghestanian & Popov piece on alma mater effects makes me glad not to be young again!

In England, a number of students who took the GCSE  mathematics test have been complaining about a question involving Hannah and her sweets. Here is the question:

There are n sweets in a bag. Six of the sweets are orange. The rest of the sweets are yellow. Hannah takes a random sweet from the bag. She eats the sweet. Hannah then takes at random another sweet from the bag. She eats the sweet. The probability that Hannah eats two orange sweets is 1/3. Show that n^2-n-90=0.

Not a difficult question. I would lengthen the last sentence to read: Use this information to show that n must satisfy the following equation. But a pointless one. It gives the study of mathematics a bad name. How is it we know there are only two colors of sweets in the bag without knowing n? How is it we know that there are only 6 orange sweets without knowing how many yellow ones there are? Why can’t I work out n by emptying the bag and counting its contents? In short, students are asked to accept an implausible premise to compute something that can be done simply by other means.

Stanford University, based in California, has once again anticipated the future. In addition to providing subsidized housing to attract and retain faculty, faculty can now choose to be paid in water. The University has quietly been buying up farms to acquire ownership of water rights and has even signed futures contracts with the Great Lakes Regional Water authority for the delivery of water 15 years from now. In addition they have a joint venture with Elon Musk, to harvest water from comets. Google meanwhile, is behind the curve. They’ve only gone as far as allowing their employees to take long showers on site.

There is a brief period in a professor’s life when they are the lion of the dinner table and toast of the town. Its when the children of their friends and contemporaries are about to enter college. To my colleagues near and far I say enjoy the attention while you can.

What advice did I offer when called upon to do so?

Don’t worry. Your child has already made the most important decision of their lives and done so correctly. They chose you as a parent.

`No, seriously, how can my child make it to a top school?’, was the invariable reply. Followed by a reminder of the ostensibly low acceptance rates at `top’ colleges. `Don’t worry,’ I would repeat, `arithmetic is on your side.’

Each year about 30,000 students apply to Harvard. About 10,000 of these will be summarily rejected on academic grounds. That leaves about 20,000. Not all of them will get into Harvard. However, most of them are applying to the same subset of schools. There are 7 Ivy League schools, plus MIT, Stanford & Caltech. Throw in the University of Chicago and Berkeley. Collectively, these institutions enroll about 20,000 students in their freshman classes. This is not counting Duke, Northwestern, Michigan and UCLA.

`But, but, isn’t all that hard work, focus and diligence wasted if they don’t get into Stanford, MIT or Harvard?’

No, those habits will serve them throughout their lives not just at admission. Admissions is a lottery among those who make the `grade’. If the `losing ticket’ is Cornell or Chicago, its a lottery with no downside! How often does life present you with with such an opportunity.

Two articles in the March 3rd, 2015 issue of the NY Times. One by the columnist Nocera marvels at Buffet’s success and concludes that it must be due to Buffet’s genius. The second, in the business section of the same, summarizes Buffet’s annual letter that attempts to explain his success. As usual, neither considers the possibility that luck may have a role in Buffet’s success. Buffet may indeed be a Vulcan, but based on the data alone one cannot reject the possibility that luck may explain Buffet’s record. I won’t repeat the argument but will point to this paper by my colleagues (Foster & Stine) that does so.

On January 30th of this year, one of the arms of the BBC reported a row at Sheffield University about an economics exam question. The offending exam question is reproduced below. Is the question, as one student suggested, indistinguishable from Chinese?

Consider a country with many cities and assume there are N > 0 people in each city. Output per person is \sigma N^{0.5} and there is a coordination cost per person of \gamma N^2. Assume that \sigma > 0 and \gamma > 0.

a) What sort of things does the coordination cost term \gamma N^2 represent? Why does it make sense that the exponent on N is greater than 1?

b) Draw a graph of per-capita consumption as a function of N and derive the optimal city size N. How does it depend on the parameters \sigma and \gamma? Provide intuition for your answers.

c) Describe which combination of \sigma and \gamma generate a peasant economy, meaning an economy with no cities (or 1-person cities). Why might the values of the parameters \sigma and \gamma have changed over time? What do these changes imply in terms of optimal city size.

Without knowing what was covered in classes and homework one cannot tell what kind of tacit knowledge/conventions the examiner was justified in assuming in posing the question. Its easy, with experience at these things, to guess what the examiner had in mind. Nevertheless, the question is badly worded and allows a `sea lawyer‘ of a student to get full marks.

First, the sentence does not assert a connection between output and coordination. Thus, the answer to (a) should be:

Without knowing the purpose of the coordination, it is impossible to answer this question.

A better first sentence would have been:

Consider a country with many cities and assume there are N > 0 people in each city. Output per person is \sigma N^{0.5} and to achieve it requires a coordination cost per person of \gamma N^2.

Second, readers are not told the units in which output is denominated. Thus, part (b) cannot be answered unless one assumes that output has a constant dollar value. One might reasonably suppose this is not the case. The sea lawyer would answer:

As output can be generated at no cost, and is monotone in city size, the optimal size of the city is infinity. Note this does not depend on the values of \sigma or \gamma.

The answer to part (c), consistent with the earlier answers:

From the answer to part (b) we see that no combination of parameters would generate a peasant economy.

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